Abstract
Diabetic retinopathy is a disease caused by vascular complications of diabetes mellitus. The more increasing number of people with diabetes mellitus every year, then indirectly the chances of someone’s eye experiencing diabetic retinopathy disorders are also increasing. Fundus photos are one way to detect diabetes mellitus in the retina of the eye. The stages used in the detection process of diabetic retinopathy include the stage of pre-processing fundus images namely grayscale and histogram equalization processes, the stage of reducing image size using Principal Components Analysis (PCA) and the stage of diabetic retinopathy detection on fundus images using fuzzy modeling network type 2. Fuzzy modeling network type 2 is a method using multilayer neural network architecture with backpropagation learning and fuzzy systems for its rules. The results of the validation system test show that the process of detecting diabetic retinopathy using the type 2 fuzzy modeling network algorithm is obtained the accuracy of 80%.
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